import json import mlflow import pandas as pd model_name = "s430705" model_version = 30 mlflow.set_tracking_uri("http://172.17.0.1:5000") model = mlflow.pyfunc.load_model( model_uri=f"models:/{model_name}/{model_version}" ) # with open('artifacts/model/input_example.json', 'r') as datafile: # data = json.load(datafile) # example_input = data["inputs"] # input_dictionary = {i: x for i, x in enumerate(example_input)} # input_ex = pd.DataFrame(input_dictionary, index=[0]) print(model.predict(input_example))